Gait Pattern in People with Multiple Sclerosis: A Systematic Review

Cardiorespiratory fitness but not cognition predicts covert worsening of gait variability over two years in people with multiple sclerosis

BACKGROUND

Gait is typically symmetrical and consistent and subtle increases in gait variability can suggest loss of neural control. In multiple sclerosis (MS), covert walking changes precede clinical signs, often not detectable on observation, and measurement of gait variability could be a potential biomarker of covert neurodegeneration. Both cognition and fitness could influence changes in gait variability. This study aimed to examine gait variability over two years in clinically stable people with MS and determine whether fitness or cognition could predict change in gait variability.

RESEARCH QUESTION

Does gait variability serve as a longitudinal biomarker in people with MS, and is fitness or cognition protective against changes in gait variability?

METHODS

49 people with stable MS (65.3 % females) were recruited from MS clinics. At the initial assessment (T1), cognition was assessed using the Montreal Cognitive Assessment, and fitness was measured as maximal oxygen update (VO2max) during a graded exercise test using a whole-body recumbent stepper. They performed self-selected walking on an instrumented walkway at initial assessment (T1) and after two years (T2), and stride time variability (STV) was measured as the coefficient of variation of stride time.

RESULTS

The average age of the participants was 45.86 ± 12.18 years, and the average time between assessments was 17.7 ± 5.0 months. The average STV was 7.33 % at T1 and increased to 8.13 % at T2 (p = 0.042). After controlling for age, sex, time between assessments, cognition and STV at T1, VO2max at T1 was a significant predictor of STV at T2 (β = -0.395, p = .014), accounting for 11.4 % of the variance. Cognition at T1 did not predict changes in STV.

SIGNIFICANCE

Lower cardiorespiratory fitness, but not cognition, predicted worsening gait variability over two years. Gait variability may be a sensitive biomarker of covert gait changes not apparent to an observer.

Health & Gait: a dataset for gait-based analysis

Acquiring gait metrics and anthropometric data is crucial for evaluating an individual's physical status. Automating this assessment process alleviates the burden on healthcare professionals and accelerates patient monitoring. Current automation techniques depend on specific, expensive systems such as OptoGait or MuscleLAB, which necessitate training and physical space. A more accessible alternative could be artificial vision systems that are operable via mobile devices. This article introduces Health&Gait, the first dataset for video-based gait analysis, comprising 398 participants and 1, 564 videos. The dataset provides information such as the participant's silhouette, semantic segmentation, optical flow, and human pose. Furthermore, each participant's data includes their sex, anthropometric measurements like height and weight, and gait parameters such as step or stride length and gait speed. The technical evaluation demonstrates the utility of the information extracted from the videos and the gait parameters in tackling tasks like sex classification and regression of weight and age. Health&Gait facilitates the progression of artificial vision algorithms for automated gait analysis.

Gait Parameters in Healthy Older Adults in Korea

OBJECTIVE

Gaits constitute the most fundamental and common form of human locomotion and are essential in daily activities. We aimed to investigate gait parameters in medically and cognitively healthy older adults to determine the independent effects of age, physical attributes, and cognition on these parameters.

METHODS

This retrospective study enrolled healthy older adult participants aged 50 years or older with normal cognition and no neurological symptoms or medical/surgical history that could affect gait. Quantitative gait analysis was conducted via the GAITRite Electronic Walkway, which categorizes gait parameters into spatiotemporal, spatial, temporal, phase, and variability. Gait parameters were compared between sexes across different age groups. The independent effects of age, Mini-Mental State Examination score, and physical characteristics were analyzed via a multiple regression model.

RESULTS

This study included 184 participants with an average age of 72.2 years. After adjusting for age, height, and footwear, only the base width and its variability differed between the sexes. Gait parameters varied significantly among different age groups, revealing multiple interparameter associations. Age was independently correlated with decreased velocity, step and stride lengths, single support time percentage and increased double support time, double support time percentage, and variability parameters, excluding the coefficient of variance of base width. Height was positively correlated with velocity, step and stride lengths, and base width, whereas leg length was negatively associated with cadence and positively associated with temporal parameters of gait.

CONCLUSION

Gait parameters in healthy older adults were not only associated with age and physical characteristics but also had interparameter correlations.

Exploring key factors associated with falls in people with multiple sclerosis: The role of trunk impairment and other contributing factors

Background

Falls are a common and consequential concern for persons with multiple sclerosis (PwMS), with trunk impairment frequently observed even in the early stages of the disease. However, the relationship between falls and trunk impairment using the trunk impairment scale in this population remains unclear. This study aims to explore this association and identify potential factors contributing to falls in PwMS.

Method

Sixty-four patients were assessed for falls or near falls in the past 6 months, trunk impairment using the Trunk Impairment Scale (TIS), balance and gait using the Performance-Oriented Mobility Assessment (POMA), depression and anxiety using the Hospital Anxiety and Depression Scale (HADS), fatigue using the Modified Fatigue Impact Scale (MFIS), and fear of falling using the Modified Falls Efficacy Scale (MFES).

Results

Simple binary logistic regression revealed significant associations for TIS (OR = 0.75, p = 0.001, 95 % CI: 0.63 to 0.88), POMA (OR = 0.75, p ≤ 0.001, 95 % CI: 0.65 to 0.87), MFES (OR = 0.96, p ≤ 0.001, 95 % CI: 0.93 to 0.98), MFIS (OR = 1.05, p = 0.002, 95 % CI: 1.02 to 1.08), and HADS (OR = 1.09, p = 0.01, 95 % CI: 1.02 to 1.17). The multiple logistic regression model identified TIS (OR = 0.78, p = 0.007, 95 % CI: 0.66 to 0.94) and MFES (OR = 0.96, p = 0.005, 95 % CI: 0.93 to 0.98) as significant factors of falls.

Conclusion

This study confirms the significant impact of trunk impairment, tested by the trunk impairment scale and fear of falling as factors of falls among PwMS. Additionally, it highlights the roles of balance, gait, fatigue, and depression as factors that contribute to fall risk. These findings suggest that a comprehensive assessment incorporating these elements may be crucial for developing effective fall prevention strategies in this population. This research underscores the need for targeted interventions that address both physical and psychological aspects to mitigate the risk of falls in PwMS.

Effect of serious games over conventional therapy in the rehabilitation of people with multiple sclerosis - a systematic review and meta-analysis

PURPOSE

This meta-analysis aimed to quantify the effect of serious games over conventional therapy on upper-limb activity, balance, gait, fatigue, and cognitive functions in people with multiple sclerosis.

MATERIALS AND METHODS

Search strategies were developed for PubMed, Embase, Cochrane Library, and Scopus. Studies were selected if participants were adults with multiple sclerosis; the intervention consisted of a virtual reality serious game-based program; the control group received conventional therapy; outcomes included upper limb activity, balance, gait, fatigue, or cognitive functions; and used a randomized controlled trial design. Data were synthesized using a standardized mean difference with a random-effects model.

RESULTS

From 2532 studies, seventeen trials were selected (n = 740). Overall, serious games programs effect on upper limb activity, gait, verbal memory, verbal fluency and attention seemed neutral. Balance functions appeared to be improved by semi-immersive virtual reality serious games (SMD = 0.48;95%CI = 0.12-0.84;p = 0.01;I2=0%), fatigue by treadmill serious games (SMD = 0.80;95%CI = 0.40-1.20;p < 0.001) and visuo-spatial memory by semi-immersive virtual reality general cognitive serious games (SMD = 0.35;95%CI = 0.04-0.65;p = 0.03;I2=0%).

CONCLUSION

This review suggests, with a very-low-to-low certainty of evidence, that while some specific serious games may improve balance, fatigue and visuo-spatial memory, their overall effect on upper limb activity, gait, and other cognitive functions appears neutral.

Brief High-Velocity Motor Skill Training Increases Step Frequency and Improves Length/Frequency Coordination in Slow Walkers With Chronic Motor-Incomplete Spinal Cord Injury

OBJECTIVE

To quantify spatiotemporal coordination during overground walking among persons with motor-incomplete spinal cord injury (PwMISCI) by calculating the step length (SL)/step frequency (SF) ratio (ie, the Walk Ratio [WR]) and to examine the effects of motor skill training (MST) on the relationship between changes in these parameters and walking speed (WS).

DESIGN

Between-day exploratory analysis.

SETTING

Research laboratory in a rehabilitation hospital PARTICIPANTS: PwMISCI (N=26).

INTERVENTIONS

3-day high-velocity MST.

MAIN OUTCOME MEASURES

Overground WS, SL, SF, and WR measured during the 10-Meter Walk Test.

RESULTS

Among the full sample, MST was associated with increases in WS, SL, SF, and a decrease in the WR. Relative change in WS and SF was higher among slow (ΔWS=↑46%, ΔSF=↑28%) vs fast (ΔWS=↑16%, ΔSF=↑8%) walkers. Change in the WR differed between groups (slow: ΔWR=↓10%; fast: ΔWR=0%). Twenty-six percent of the variability observed in ΔWR among slow walkers could be explained by ΔSF, while ΔSL did not contribute to ΔWR. Among fast walkers, ΔSL accounted for more than twice the observed ΔWR (43%) compared to ΔSF (15%).

CONCLUSIONS

On the whole, WR values among PwMISCI are higher than previous reports in other neurologic populations; however, values among fast walkers were comparable to noninjured adults. Slow walkers demonstrated greater variability in the WR, with higher values associated with slower WS. Following MST, increases in WS coincided with a decrease in the WR among slow walkers, mediated primarily through an effect on SF. This finding may point to a specific mechanism by which MST facilitates improvements in WS among PwMISCI with greater mobility deficits.

Unobtrusive measurement of gait parameters using seismographs: An observational study

Analyzing irregularities in walking patterns helps detect human locomotion abnormalities that can signal health changes. Traditional observation-based assessments have limitations due to subjective biases and capture only a single time point. Ambient and wearable sensor technologies allow continuous and objective locomotion monitoring but face challenges due to the need for specialized expertise and user compliance. This work proposes a seismograph-based algorithm for quantifying human gait, incorporating a step extraction algorithm derived from mathematical morphologies, with the goal of achieving the accuracy of clinical reference systems. To evaluate our method, we compared the gait parameters of 50 healthy participants, as recorded by seismographs, and those obtained from reference systems (a pressure-sensitive walkway and a camera system). Participants performed four walking tests, including traversing a walkway and completing the timed up-and-go (TUG) test. In our findings, we observed linear relationships with strong positive correlations (R2 > 0.9) and tight 95% confidence intervals for all gait parameters (step time, cycle time, ambulation time, and cadence). We demonstrated that clinical gait parameters and TUG mobility test timings can be accurately derived from seismographic signals, with our method exhibiting no significant differences from established clinical reference systems.

Investigation of parameters related to lower extremity muscle strength and proprioception in Patients with Multiple Sclerosis: a cross-sectional study

BACKGROUND

Patients with Multiple Sclerosis (PwMS) may experience a decline in balance, gait, and mobility as well as an increase in fear of falling (FoF) and fatigue due to weaker muscles and proprioceptive loss in their lower limbs. The study aimed to compare lower extremity muscle strength and proprioception, balance, functional mobility, gait, FoF, and fatigue between PwMS and healthy controls and to investigate the relationship between lower extremity muscle strength and proprioception and balance, functional mobility, gait, FoF, and fatigue in PwMS.

METHODS

The study was completed with 35 PwMS and 35 healthy controls with matching age and gender. The 5 Repetition Sit-to Stand Test (5-STS-test), knee and ankle reposition tests (using a digital inclinometer), the Berg Balance Scale (BBS), the Timed Up and Go (TUG) test, the Dynamic Gait Index (DGI), the Falls Efficacy-International (FES-I), and the Fatigue Severity Scale (FSS) were used for evaluations.

RESULTS

The 5-STS test, knee and ankle reposition tests, TUG, FES-I, and FSS Test scores were higher and BBS and DGI scores were lower in PwMS compared to healthy controls (p < 0.05). BBS, DGI, TUG, FES-I, and FSS were associated with 5-STS test and knee and ankle reposition tests except for some nondominant reposition tests in PwMS (r between 0.342 and -0.714; p < 0.05 for all).

CONCLUSION

Lower extremity muscle strength and proprioception were associated with balance, functional mobility, gait, FoF, and fatigue in PwMS. These results suggested that detailed assessment of neuromuscular parameters in lower extremity function is important in determining the appropriate rehabilitation programs.

Kinematic Gait Analysis in People with Mild-Disability Multiple Sclerosis Using Statistical Parametric Mapping: A Cross-Sectional Study

Multiple sclerosis (MS) is a chronic autoimmune disease that affects the central nervous system. Gait abnormalities, such as altered joint kinematics, are common in people with MS (pwMS). Traditional clinical gait assessments may not detect subtle kinematic alterations, but advances in motion capture technology and analysis methods, such as statistical parametric mapping (SPM), offer more detailed assessments. The aim of this study was to compare the lower-limb joint kinematics during gait between pwMS and healthy controls using SPM analysis. Methods: A cross-sectional study was conducted involving pwMS and healthy controls. A three-dimensional motion capture system was used to obtain the kinematic parameters of the more affected lower limb (MALL) and less affected lower limb (LALL), which were compared using the SPM analysis. Results: The study included 10 pwMS with mild disability (EDSS ≤ 3) and 10 healthy controls. The results showed no differences in spatiotemporal parameters. However, significant differences were observed in the kinematics of the lower-limb joints using SPM. In pwMS, compared to healthy controls, there was a higher anterior pelvis tilt (MALL, p = 0.047), reduced pelvis elevation (MALL, p = 0.024; LALL, p = 0.044), reduced pelvis descent (MALL, p = 0.033; LALL, p = 0.022), reduced hip extension during pre-swing (MALL, p = 0.049), increased hip flexion during terminal swing (MALL, p = 0.046), reduced knee flexion (MALL, p = 0.04; LALL, p < 0.001), and reduced range of motion in ankle plantarflexion (MALL, p = 0.048). Conclusions: pwMS with mild disability exhibit specific kinematic abnormalities during gait. SPM analysis can detect alterations in the kinematic parameters of gait in pwMS with mild disability.

Deep Learning for Multiple Sclerosis Differentiation Using Multi-Stride Dynamics in Gait

OBJECTIVE

Multiple sclerosis (MS) is a chronic neurological condition of the central nervous system leading to various physical, mental and psychiatric complexities. Mobility limitations are amongst the most frequent and early markers of MS. We evaluated the effectiveness of a DeepMS2G (deep learning (DL) for MS differentiation using multistride dynamics in gait) framework, which is a DL-based methodology to classify multi-stride sequences of persons with MS (PwMS) from healthy controls (HC), in order to generalize over newer walking tasks and subjects.

METHODS

We collected single-task Walking and dual-task Walking-while-Talking gait data using an instrumented treadmill from a balanced collection of 20 HC and 20 PwMS. We utilized domain knowledge-based spatiotemporal and kinetic gait features along with two normalization schemes, namely standard size-based and multiple regression normalization strategies. To differentiate between multi-stride sequences of HC and PwMS, we compared 16 traditional machine learning and DL algorithms. Further, we studied the interpretability of our highest-performing models; and discussed the association between the lower extremity function of participants and our model predictions.

RESULTS

We observed that residual neural network (ResNet) based models with regression-based normalization were the top performers across both task and subject generalization classification designs. Considering regression-based normalization, a multi-scale ResNet attained a subject classification accuracy and F 1-score of 1.0 when generalizing from single-task Walking to dual-task Walking-while-Talking; and a ResNet resulted in the top subject-wise accuracy and F 1 of 0.83 and 0.81 (resp.), when generalizing over unseen participants.

CONCLUSION

We used advanced DL and dynamics across domain knowledge-based spatiotemporal and kinetic gait parameters to successfully classify MS gait across distinct walking trials and unseen participants.

SIGNIFICANCE

Our proposed DL algorithms might contribute to efforts to automate MS diagnoses.

Gait Analysis in Neurorehabilitation: From Research to Clinical Practice

When brain damage occurs, gait and balance are often impaired. Evaluation of the gait cycle, therefore, has a pivotal role during the rehabilitation path of subjects who suffer from neurological disorders. Gait analysis can be performed through laboratory systems, non-wearable sensors (NWS), and/or wearable sensors (WS). Using these tools, physiotherapists and neurologists have more objective measures of motion function and can plan tailored and specific gait and balance training early to achieve better outcomes and improve patients' quality of life. However, most of these innovative tools are used for research purposes (especially the laboratory systems and NWS), although they deserve more attention in the rehabilitation field, considering their potential in improving clinical practice. In this narrative review, we aimed to summarize the most used gait analysis systems in neurological patients, shedding some light on their clinical value and implications for neurorehabilitation practice.

Complementary use of statistical parametric mapping and gait profile score to describe walking alterations in multiple sclerosis: a cross-sectional study

Gait analysis is often used to study locomotor alterations in people with multiple sclerosis (PwMS), but the large number of extracted variables challenges the interpretability. In this paper, we analysed gait alterations by combining the Gait Profile Score (GPS), which summarizes kinematic locomotor deviations, and Statistical Parametric Mapping (SPM), which compares kinematics and kinetics over the whole gait cycle. Eleven PwMS and 11 speed-matched Healthy Controls (HC) underwent overground gait analysis. GPS were compared through independent-samples t-tests; sagittal-plane kinematics and power at hip, knee, and ankle were compared through SPM Hotelling's-T2 and SPM t-tests. Spearman's correlation coefficients (r) between GPS and clinical outcomes were also calculated. PwMS had higher GPS than HC (PwMS = 8.74 ± 2.13°; HC = 5.01 ± 1.41°;p < 0.001). Multivariate SPM found statistically significant differences at 0-49%, 70-80%, and 93-99% of stride (p < 0.05) and univariate analysis showed reduced ankle dorsiflexion, and lower knee flexion during pre-swing and swing. GPS correlated with Expanded Disability Status Scale (r = 0.65; 95%C.I.[0.04,0.91]; p = 0.04) and 2-Minute Walking Test (r = -0.65; 95%C.I.[-0.91,-0.04]; p = 0.04). GPS in conjunction with SPM revealed multi-joint kinematic alterations on sagittal plane involving distal joint angles, ankle and knee, during the stance phase with no changes at the proximal level. Gait deviations were more pronounced in PwMS with higher disability and walking limitations.

Muscle Coactivation Index during Walking in People with Multiple Sclerosis with Mild Disability, a Cross-Sectional Study

BACKGROUND

Multiple sclerosis (MS) is a progressive neurodegenerative disease characterized by axonal degeneration and demyelination. Changes in gait, related to joint kinematics and kinetics, especially at the ankle and knee, have been observed in people with MS (pwMS). Muscle coactivation plays an important role in joint stabilization; however, excessive coactivation may interfere with gait. The aim of this study was to analyze the differences in muscle activation during gait in pwMS compared to healthy individuals.

METHODS

A cross-sectional study was conducted involving pwMS and healthy controls. Surface electromyography was used to record muscle activity during gait. The main outcome measures were the coactivation index (CI) and the area under the curve (AUC), which were calculated for several pairs of lower extremity muscles.

RESULTS

Nine pwMS and nine healthy controls were included. When comparing the MS group to the control group, the AUC was significantly higher in the lateral gastrocnemius (p = 0.023) and the CI for the lateral gastrocnemius-anterior tibialis (p = 0.022) and gluteus maximus-lateral gastrocnemius (p = 0.047).

CONCLUSION

Mildly affected pwMS have altered muscle coactivation patterns during gait, especially in the most affected limb. The results highlight the importance of muscle coactivation in pwMS and its possible role in the early detection of gait abnormalities.

[Knee range of motion as a marker of the effectiveness of medical intervention in multiple sclerosis]

OBJECTIVE

To measure the knee range of motion (ROM) in the sagittal plane by video analysis in patients with multiple sclerosis (MS) after a course of medical rehabilitation and determine the minimal clinically important differences (MCID).

MATERIAL AND METHODS

We examined 45 patients (37 women, 8 men) with relapsing-remitting (n=38) and secondary-progressive MS before and after a course of medical rehabilitation. Gait parameters were recorded on video analysis system Physiomed Smart («Physiomed», Germany, the Davis protocol).

RESULTS

The course of complex medical rehabilitation contributes to an increase knee ROM in MS patients in a wide range of disability (EDSS <6.5 points). MCID is estimated as 7.14° in mild (EDSS ≤4.0) and as 7.67° in moderate (EDSS=4.5-5.5) gait impairment.

CONCLUSION

The results will assist clinicians and researchers in interpreting the significance of observed kinematic changes in the knee joint in MS patients after medical intervention.

Acute effects of axial loading on postural control during walking and turning in people with multiple sclerosis: A pilot study

BACKGROUND

Impaired sensory integration is heavily involved in gait control and accentuates fall risk in individuals with multiple sclerosis (MS). While axial loading has been found beneficial, little is known about the effect of non-specific axial loads on gait parameters and mobility tasks in those with MS.

RESEARCH QUESTION

What are the effects of non-specific axial loading via weighted vests on walking and turning in those with MS.

METHODS

Twelve participants with MS and eleven age- and gender-matched healthy controls participated in a cross-sectional study. All participants completed five trials of continuous walking with turns wearing weighted vests at 0%, 2%, 4%, 5%, and then 0% of their body weight. Gait parameters were measured using wireless inertial sensors. A 2 (group) x 5 (vest weight) multivariate analysis of variance (MANOVA) was performed to determine any significant differences between groups and across weighted vests for each gait variable. Post-hoc analysis and paired t-tests with corresponding effect sizes were also conducted.

RESULTS

A significant between groups main effect was found for group (F (6100) = 14.74, p = .000) in multiple gait parameters (p < 0.05), although no significant main effect was found for weighted vest. Within group analyses indicated significantly increased cadence and gait speed across varying weighted vests for both MS and control groups (p < 0 >05). Increased vest weight from 0%PRE to 2% also had large effect on shortening double support time and increasing stride length in the MS group.

SIGNIFICANCE

This study provided preliminary evidence that non-specific axial loads of varying weights appear to improve certain gait parameters. As such, this modality may offer mobility benefit and serve as an accessible home-based intervention alternative aimed at improving walking in individuals with MS.

The Timing of Kinematic and Kinetic Parameters during Gait Cycle as a Marker of Early Gait Deterioration in Multiple Sclerosis Subjects with Mild Disability

This study aimed to evaluate walking in multiple sclerosis (MS) patients with mild disability. A case control study with 8 mild disability MS patients and 10 controls was conducted. This study analyzed spatiotemporal, kinematic, and kinetic parameters. We also analyzed the timing of these parameters, as a percentage of the gait cycle. The MS patients and controls walked with a similar gait pattern. However, there were differences in the timing of the biomechanical parameters. The timing of toe-off was at 62–63% of gait cycle in MS subjects while in controls it was at 59.94% (p = 0.009 to 0.027 vs. to controls). The peak of knee flexion during swing was at 74–76% of gait cycle in MS subjects while in controls was at 72% (p = 0.027 to 0.034). While the peak of ankle dorsiflexion during stance occurred at 48–50% in MS subjects, while in controls it was at 46% (p = 0.001 to 0.009), and the peak of plantar flexion during pre-swing was at 66% in MS subjects vs. 64% in controls (p = 0.001). At the kinetic pattern, the first peak of the vertical ground reaction force occurred at 14% of gait cycle in controls while in MS patients it was at 17–20% (p = 0.012 to 0.021). MS subjects with mild disability walked with similar spatiotemporal parameters, joint angles and moments compared to controls. However, our results suggest that those changed the temporal occurrences, expressed as percentage of the gait cycle, of the kinematic and kinetic parameters.

Reflex Locomotion Therapy for Balance, Gait, and Fatigue Rehabilitation in Subjects with Multiple Sclerosis

This study evaluates the effects of a rehabilitation program based on reflex locomotion therapy (RLT) on balance, gait, and fatigue in patients with multiple sclerosis (MS). Twenty-three patients diagnosed with MS participated in this study. Reversal design was carried out. The assessment tools included the Berg Balance Scale (BBS), the Performance Oriented Mobility Assessment (POMA), the Fatigue Severity Scale (FSS) and the instrumental analysis of the gait recorded by Vicon Motion System^®. We analyzed spatio-temporal parameters and kinematic variables of the hip, knee, and ankle joints. Additionally, the Client Satisfaction Questionnaire (CSQ-8) was administrated. We did find a significant improvement in balance and gait tools after the RLT period. Regarding instrumental analysis, the statistical analysis of spatio-temporal parameters showed a significant improvement in stride length, double support, and velocity after the RLT period. Concerning kinematic parameters, the analysis showed improvements in hip and knee range of motion (ROM) after RLT period. RLT could improve gait and balance in patients with MS. The patients reported a high level of satisfaction with the therapy received.